Eight-day consumption of inulin added to a yogurt breakfast lowers postprandial appetite ratings but not energy intakes in young healthy females: a randomised controlled trial
Bibliographic record
Abstract
Increasing feelings of satiety may reduce appetite and energy intake. The role of inulin consumption in impacting satiety is unclear. A randomised double-blind controlled crossover trial aimed to determine the effects of inulin+yogurt on satiety after 1 and 8-d consumption. The preload breakfast included 100 g vanilla yogurt with (yogurt-inulin (YI)) and without (yogurt-control (YC)) 6 g inulin. A total of nineteen healthy females (22·8 (sd 2·7) years) with non-restrained eating behaviour and taking hormonal contraceptives participated in the study. Day 1 and 8 visual analogue scale (VAS) ratings of Hunger, Fullness, Desire to Eat and Prospective Food Consumption (PFC) were collected at fasting and every 30 min for 180 min. Energy intake was calculated from a weighed ad libitum lunch and remainder of day food records. Total AUC was calculated for each VAS. Day 1 (VAS only) and 8 (VAS and energy intakes) data were compared between YI and YC using ANCOVA, and ANOVA was used to compare energy intakes on Day 1. There were no significant differences between Day 1 YI and YC AUC appetite ratings or energy intakes. However, 8-d consumption of YI v. YC was associated with lower Desire to Eat and PFC ratings but similar lunch and total day energy intakes. Therefore, the addition of 6 g inulin to a commercially available yogurt affected feelings of appetite, but not energy intake, after repeated consumption. These results suggest that inulin may be a suitable ingredient to increase dietary fibre consumption, with potential to impact appetite.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".